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Introduction to the analysis of community data

Introduction to the analysis of community data. Vojtech Novotny Czech Academy of Science, University of South Bohemia & New Guinea Binatang Research Center . Ecological analysis of community samples. typical data format:. Some of the questions you can ask about the samples: How many species?

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Introduction to the analysis of community data

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  1. Introduction to the analysis of community data Vojtech Novotny Czech Academy of Science, University of South Bohemia & New Guinea Binatang Research Center

  2. Ecological analysis of community samples typical data format:

  3. Some of the questions you can ask about the samples: How many species? How many individuals? What species are common / rare? How different are the sites in their species composition? How different are the species in their distribution?

  4. Presence – absence characteristics: number of species and sites

  5. Species accumulation curve

  6. How many species? Corrected estimate for missing species Chao1 S + singletons2/(2*doubletons) S – number of species sampled

  7. Courtesy Jonathan Coddington . .

  8. Courtesy Jonathan Coddington

  9. No. of species often depends on the number of individuals: samples with more individuals have also more species Rarefraction: Comparing the number of species in a random selection of the same number of individuals from each sample

  10. Diversity measures: describing distribution of individuals among species Simpson’s index: the probability that two individuals chosen from your sample will belong to the same species Berger-Parker’s index: share of the most common species

  11. Diversity estimate: Simpson’s diversity: 1- ∑[ni(ni-1)/N(N-1)] ni – number of individuals from species i, N – total number of individ. Berger-Parker’s Index: nmax/N nmax = abundance of the most common species, N – total no. of individ.

  12. Alpha, beta and gamma diversity alpha diversity beta diversity gamma diversity  = avg+  avg = 16.6  = 20 • = 20 - 16.6 = 3.4 α β γ

  13. Community similarity estimate: Jaccard similarity: shared species/[total species X + Y] Jaccard similarity= A/(A+B+C) X, Y - samples X Y

  14. Similarity indices Koleff et al. 2003 J anim Ecol 72:367

  15. EstimateS data format, saved as TXT file

  16. Chao1 S + singletons2/(2*doubletons) S = number of species sampled Jaccard CJ CJ = a / (a + b + c) a = richness in first site, b = richness in second site, j = shared species Sorenson CS CS = 2a / (2a + b +c) Simpson's Index (D) measures the probability that two individuals randomly selected from a sample will belong to the same species

  17. Jaccard Coefficient • number of shared species as proportion of total number of species in the two SUs • ranges from 0 (no species in common) to 1 (the SUs have identical species lists)

  18. Sørenson Coefficient • like Jaccard, ignores shared absences

  19. Quantitative Version of Sørenson (Bray-Curtis) Similarity

  20. Morisita-Horn CmH • Not influenced by sample size & richness • Highly sensitive to the abundance of common spp. • CmH = 2S(ani * bni) / (da + db)(aN)(bN) • aN = total # of indiv in site A • ani = # of individuals in ith species in site A • da = Sani2 / aN2

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